目的:在本研究中,我们采用生物信息学方法来鉴定舌鳞状细胞癌(TSCC)的诊断生物标志物,并研究TSCC中免疫细胞的浸润,以及生物标志物和免疫细胞之间的关系。
方法:我们从数据库中获得了TSCC表达数据集,并使用R软件在TSCC和邻近正常组织之间进行了差异基因表达分析。使用DAVID网站进行差异表达基因(DEGs)的富集分析。构建了DEGs的蛋白质相互作用网络,使用STRING和Cytoscape等工具鉴定了hub基因。进行存活分析以鉴定诊断性生物标志物,并且使用具有Cibersort软件的逆卷积算法分析TSCC中的免疫细胞的浸润。最后,通过临床病理切片证实了所发现分子的表达。
结果:我们确定了TSCC中的24度,主要与信号转导有关,物质代谢,先天免疫反应,和其他相关的信号通路。在通过构建蛋白质-蛋白质相互作用(PPI)网络筛选的24个hub基因中,七(MMP13,POSTN,MMP9,MMP10,MMP3,SPP1,MMP1)具有预后价值。生存分析表明SPP1具有诊断潜力。SPP1基因的表达水平与TSCC以及几种免疫细胞类型有关,包括巨噬细胞M0,M1,M2,CD8+T细胞,激活的NK细胞,和单核细胞(p<0.05)。组织学结果证实,与邻近的非癌组织相比,TSCC组织中SPP1的表达更高,特别是在表达CD68的巨噬细胞中。
结论:我们的研究结果表明,SPP1作为TSCC的诊断生物标志物,并参与TSCC组织内的免疫细胞浸润。SPP1与巨噬细胞之间的相关性可能为TSCC的靶向治疗研究提供新的见解。
OBJECTIVE: In this study, we employed a bioinformatics approach to identify diagnostic biomarkers for tongue squamous cell carcinoma (TSCC) and investigate the infiltration of immune cells in TSCC, as well as the relationship between biomarkers and immune cells.
METHODS: We obtained the TSCC expression dataset from a database and conducted differential gene expression analysis between TSCC and adjacent normal tissues using R software. Enrichment analysis of the differentially expressed genes (DEGs) was performed using the DAVID website. Protein interaction networks for the DEGs were constructed, and hub genes were identified using tools such as STRING and Cytoscape. Survival analysis was conducted to identify diagnostic biomarkers and the infiltration of immune cells in TSCC was analyzed using the inverse convolution algorithm with Cibersort software. Finally, the expression of the discovered molecules was verified through clinical pathological sections.
RESULTS: We identified 24 DEGs in TSCC, primarily associated with signal transduction, substance metabolism, innate immune response, and other related signaling pathways. Among the 24 hub genes screened through the construction of a protein-protein interaction (PPI) network, seven (MMP13, POSTN, MMP9, MMP10, MMP3, SPP1, MMP1) exhibited prognostic value. Survival analysis indicated that SPP1 demonstrated diagnostic potential. The expression level of the SPP1 gene showed a correlation with TSCC as well as several immune cell types, including macrophage M0, M1, M2, CD8+ T cell, activated NK cell, and monocyte (p < 0.05). Histological results confirmed higher expression of SPP1 in TSCC tissues compared to adjacent non-cancerous tissues, particularly in CD68-expressing macrophages.
CONCLUSIONS: Our findings suggest that SPP1 serves as a diagnostic biomarker for TSCC and is involved in immune cell infiltration within TSCC tissues. The correlation between SPP1 and macrophages may offer new insights for targeted therapeutic research on TSCC.